摘要
针对车型识别技术存在类别判定冲突问题,提出基于相容系数的多传感器融合目标识别方法。首先,采用多假设思想实现多传感器异构数据聚类合并获取单帧融合检测结果;然后,计算证据之间的相容系数对证据冲突重新分配,结合Dezert-Smarandache理论(DSmT)来处理单帧融合后可能出现的证据冲突情况,并获取目标类别的准确识别结果。实测数据结果表明,该方法能克服传感器检测范围受限问题和类别判定冲突问题,目标识别准确率可达93%以上,降低了目标识别的漏检率和误检率,可达到良好的目标识别准确性能。
Aiming at the problem of class determination conflict in vehicle recognition technology,a multi-sensor fusion target recognition method based on compatibility coefficient is proposed.Firstly,multi-hypothesis thinking is used to realize multi-sensor heterogeneous data clustering and merging to obtain single-frame fusion detection results;then,the compatibility coefficient between evidences is calculated to redistribute evidence conflicts,and the single-frame processing is combined with Dezert-Smarandache theory(DSmT)conflicts of evidence that may arise after fusion,and obtain accurate identification results of the target category.The results of actual measurement data show that this method can overcome the problem of limited sensor detection range and conflict of category determination,and the target recognition accuracy rate can reach more than 93%,which reduces the missed detection rate and false detection rate of target recognition,and can achieve good target recognition accurate performance.
作者
文礼杰
谢荣
许军立
刘峥
Wen Lijie;Xie Rong;Xu Junli;Liu Zheng(National Laboratory of Radar Signal Processing,Xidian University,Xi′an 710071,China;Shenzhen Leishen Intelligent System Co.,Ltd.,Shenzhen 518104,China)
出处
《电子测量与仪器学报》
CSCD
北大核心
2023年第4期142-153,共12页
Journal of Electronic Measurement and Instrumentation
基金
国家自然科学基金(62001346)
CASC多传感器探测与识别技术研发中心种子基金(ZZJJ202102)项目资助。
关键词
多传感器融合
相容系数
多假设思想
DSMT
改进证据冲突重分配
multi-sensor fusion
compatibility coefficient
multi-hypothetical thinking
DSmT
improved evidence conflict redistribution